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Slide1
Chapter
5Brief history of climate: causes and mechanisms
Climate
system dynamics and
modelling Hugues GoosseSlide2
Chapter 5 Page
2
Outline
Investigation of the
role of
the external
forcing and of the internal dynamics.
Analysis of key
periods
to
illustrate
dominant processes.Slide3
Chapter 5 Page
3
Forced and internal variability
Forced variability
: driven by changes in external forcing
Internal variability
: caused
by interactions between various elements of the
systemSlide4
Chapter 5 Page
4
Forced and internal variability
Forced variability
: possible to find the
ultimate cause
of the observed changes
Internal variability
: only the chain of events can be identified, the
proximate cause
.Slide5
Chapter 5 Page
5
Forced and internal variability
The climate system is sensitive to
small perturbations
.Slide6
Chapter 5 Page
6
Forced and internal variability
The climate system is sensitive to
small perturbations
.
Consequences:
The skill of weather forecasts
is limited in time.
Two simulations
include different
realisations
of internal variability.
An agreement between simulations and observations
on the
timing of unforced events
is not expected on the long term.Slide7
Chapter 5 Page
7
Forced and internal variability
The
magnitude of internal variability
is a strong function of the spatial and temporal scale investigated.
Median of the standard deviation of the annual mean surface air temperature from control simulations performed in the framework of CMIP5. Figure from E. Hawkins updated from Hawkins and Sutton (2012). Slide8
Chapter 5 Page
8
Timescales of climate variations
The
timescale
of climate variations is set up by both the
forcing and internal
dynamics
.
Schematic representation of the dominant timescales of
selected
external forcing and processes related to internal dynamics
which affect climate
. Slide9
Chapter 5 Page
9
El Niño-Southern Oscillation
In normal conditions
, the thermocline is much deeper in the West Pacific than in the East Pacific.
In El Niño conditions
, the intensity of the upwelling is reduced in the East Pacific and the SST warms in the East Pacific.
Figure from Christensen et al. (2013)Slide10
Chapter 5 Page
10
El Niño-Southern Oscillation
The Walker circulation is associated
with a
positive feedback, called the
Bjerknes
feedback
.Slide11
Chapter 5 Page
11
El Niño-Southern Oscillation
The
atmospheric circulation
and
sea surface
temperature exhibit irregular
oscillations:
El Niño Southern Oscillation (
ENSO
).
Time series of the temperature in the eastern equatorial Pacific (averaged over the area 5°N-5°S-170°W-120°W, the so-called Niño3.4 index) and the SOI
index (normalized difference between SLP in Tahiti and Darwin).
Source: http://www.cpc.ncep.noaa.gov/data/indices/
. Slide12
Chapter 5 Page
12
El Niño-Southern Oscillation
ENSO is also associated with nearly global scale perturbations
.
Correlation between the sea surface temperature in the eastern tropical Pacific (Niño3.4 index) and sea-level pressure in
January.
. Slide13
Chapter 5 Page
13
The North Atlantic Oscillation
The mid-latitude westerlies in the North Atlantic present irregular changes in their intensity and in the location of their
maximum.
Correlation
between the winter NAO index and the winter SLP (average over December, January, February
).Slide14
Chapter 5 Page
14
The North Atlantic Oscillation
The NAO is associated with changes in many atmospheric and oceanic
variables.
Correlation (top) and regression in °C (bottom) between the winter NAO index and the winter surface air temperature (average over December, January, February
).
Correlation NAO index-winter temperatures
Regression NAO index-winter temperaturesSlide15
Chapter 5 Page
15
The Atlantic multidecadal oscillation and the Pacific decadal oscillation
The sea surface temperature
is
characterized by pronounced decadal and multidecadal variations.
Regression
between PDO and AMO indices with annual sea surface temperature. Figure from Hartmann et al. (2014). Slide16
Chapter 5 Page
16
Reconstructing past climates
Past climate variations can be
reconstructed
using the signal
recorded in
natural archives
by various
sensors
.
Schematic illustration of the forward and inverse approaches. Slide17
Chapter 5 Page
17
Reconstructing past climates
Dating methods
Annual layer counting.
5 cm-long section from the lake sediment of Cape Bounty, East Lake, Nunavut,
Canada. Picture from
François
Lapointe
. Slide18
Chapter 5 Page
18
Reconstructing past climates
Dating methods
Radiometric
dating: based on the decay of
radioactive
isotopes.
The decay follows a standard law:
concentration of radioisotopes
at
time
t
initial concentration
at
time
t
=0
decay constant of the radioactive isotope Slide19
Chapter 5 Page
19
Reconstructions
based on isotopes
Oxygen isotopes
The abundance of isotopes is measured using
the delta
value.
18
O
is
the ratio of
18
O
and
16
O
isotopes in the sample, compared to a
standard.Slide20
Chapter 5 Page
20
Reconstructions
based on isotopes
Oxygen isotopes
Isotopic fractionation takes place during evaporation and condensationSlide21
Chapter 5 Page
21
Reconstructions
based on isotopes
Carbon isotopes
During photosynthesis,
12
C is taken preferentially to
13
C because it is
lighter.
Organic matter has a low (negative)
d
13
C.Slide22
The Climate since the Earth’s formation
The uncertainties on Earth’ climate are larger as we go back in time
.
A simplified geological time scale.
Slide23
Chapter 5 Page
23
Precambrian climate
4
billion years ago, the solar irradiance was about
25-30
% lower than at present but the Earth was not totally ice covered : the
“faint
young Sun
paradox”.
Main
hypothesis:
a
much stronger greenhouse effect
caused by a much higher
CO
2
(250
times the present-day
value?)
and
CH
4
concentration
.Slide24
Chapter 5 Page
24
Precambrian climate
Atmospheric
composition has been modified with
time.
The photosynthesis induced
a
large increase in the atmospheric oxygen concentration 2.2. to 2.4 billion years ago
.
This
caused a glaciation
?Slide25
Chapter 5 Page
25
Precambrian climate
Large glaciations took place around 550
to 750 million years ago.
Formation of a
Snowball
Earth
around 635 million years ago
?
If this is really occurred, why does not Earth not stay permanently in this state ?Slide26
Chapter 5 Page
26
Phanerozoic climate
The
carbon cycle and climate
appear strongly
linked on
timescales of millions of
years.
Changes
in
atmospheric CO
2
concentration
can be
represented
by:
Silicate
weathering and calcium carbonate sedimentation in the ocean
Outgassing
of CO
2
due to metamorphism and
volcanic eruptions
Long-term
burial of organic matterSlide27
Chapter 5 Page
27
Phanerozoic climate
The models based on this balance are able to reproduce the
long term
changes in the carbon cycle.
Comparison of the
CO
2
concentration
calculated by GEOCARBSULF model for varying climate sensitivities (noted
D
T(2x)
on the figure) to an independent CO
2
record based on different proxies
.
Figure from Royer et al. (2007).
Large influence of climate sensitivitySlide28
Chapter 5 Page
28
Cenozoic climate
The temperature over
the last 65 million
years has
gradually decreased
. This
is associated with a cooling that is often referred to as a transition from a greenhouse climate to an icehouse
.
The global climate over the past 65 million years based on deep-sea oxygen-isotope
measurements.
Figure
from
Zachos
et al. (2008
).Slide29
Chapter 5 Page
29
Cenozoic climate
During the
Paleocene Eocene Thermal Maximum
(
PETM, 55 million years ago)
global
temperature increased by more than 5°C in about
10
000
years.
Carbonate carbon isotope
and
o
xygen
isotope ratio
in two cores in
the South Atlantic. The time on the x axis starts at the onset of the PETM about 55 million years ago.
Figure
from
McInerney
and Wing (2011). Slide30
Chapter 5 Page
30
Cenozoic climate
50
million years ago, the location of the continents was quite close to that of the present-day one but
changes in boundary conditions still had an influence on climate.
Land configuration about 60 million years
ago
. Map from Ron
BlakeySlide31
Chapter 5 Page
31
Cenozoic climate
Large
climate fluctuations have occurred over the last 5 million years
.
Benthic
18O, which measures global ice volume and deep ocean
temperature.
Data from
Lisiecki
and
Raymo
(2005).Slide32
Chapter 5 Page
32
The last million years: glacial interglacial cycles
The
characteristics of the Earth’s orbit are determined by three
astronomical parameters
.
eccentricity
(
ecc
)
obliquity
(
e
obl
), Slide33
Chapter 5 Page
33
The last million years: glacial interglacial cycles
The
climatic precession
is
ecc
sin (PERH) =
ecc
sin (
w
)
Slide34
The last million years: glacial interglacial cycles
Because of the
climatic precession
, the Earth was closest to the sun during the boreal summer 11
ka
ago and the closest to the sun during boreal winter
now.
Chapter 5 Page
34Slide35
The last million years: glacial interglacial cycles
The astronomical parameters
are varying
through time.
Long-term variations in eccentricity, climatic precession and obliquity (in
degrees). zero
corresponds to 1950
AD. Computed
from Berger (1978). Figure from Marie-France Loutre.
Chapter 5 Page
35Slide36
The last million years: glacial interglacial cycles
Eccentricity
. The
annual mean energy received by the Earth
is inversely proportional
to:
The differences
in the annual mean radiations received by the
Earth are
small
: maximum variation of 0.15
%,
i.e., 0.5
W m
-2
.
Chapter 5 Page
36Slide37
The last million years: glacial interglacial cycles
The
obliquity
has a large impact on the seasonal distribution of insolation in
polar regions
.
Chapter 5 Page
37
Changes in insolation in W m
-2
caused by
an
increase in the obliquity from 22.0° to 24.5° with
ecc
=0.016724,
PERH=102.04
, i.e. the present-day values. Figure from Marie-France LoutreSlide38
The last million years: glacial interglacial cycles
The
climatic precession
has a large impact on the
seasonal
cycle
of insolation.
Chapter 5 Page
38
Changes in insolation in W m
-2
caused by
a
decrease of the climatic precession from its maximum value (boreal winter at perihelion) to its minimum value (boreal summer at perihelion) with
ecc
=
0.016724,
e
obl
=23.446
°, i.e. the present-day values. Figure from Marie-France LoutreSlide39
The last million years: glacial interglacial cycles
The
last
800 kyr
are characterized by the
alternation between
long glacial periods
and
relatively
brief interglacials
.
Variations
in the atmospheric concentrations of CO
2
(in ppm,
and in
deuterium in Antarctica Dome C (EDC) ice core (
δ
D in ‰,
Jouzel
et al., 2007).
CO
2
concentration
Cold
Warm
Deuterium
Chapter 5 Page
39Slide40
The last million years: glacial interglacial cycles
The latest glacial period culminates about 21
ka
ago:
the Last Glacial Maximum
(LGM).
Reconstruction of the difference in surface air temperature between the Last Glacial Maximum and preindustrial
conditions. Figure
from Annan and Hargreaves (2013).
Chapter 5 Page
40Slide41
The last million years: glacial interglacial cycles
The
astronomical theory
of paleoclimate
assumes that glacial
interglacial-cycles
are
driven
by the
changes in the
astronomical
parameters.
Chapter 5 Page
41
The
summer insolation at high northern
latitudes
appears
to be of critical importance. Slide42
The last million years: glacial interglacial cycles
The
dominant
frequencies
of the
astronomical parameters
are also found in many proxy records of past climate
changes.
Chapter 5 Page
42
Models
driven by past
changes
in orbital parameters and by the observed evolution of greenhouse
gases
reproduced quite well the estimated past ice volume variations .
The
astronomical theory
of
paleoclimate.
However, the link between climate change and insolation is far from being simple and linear. Slide43
The last million years: glacial interglacial cycles
Insolation
at 66°N at the June solstice (in
W m
-2
, red) according to Berger (1978
), anomaly
of Antarctic temperature reconstructed from the deuterium record
(
blue) and in the simulation of
Ganopolski
and
Calov
(2011) (
green), Sea
level reconstructed by
Elderfield
et al. (2012) (blue) and deduced from the change in continental ice volume simulated in
Ganopolski
and
Calov
(2011) (green).
Chapter 5 Page
43
The
astronomical theory
of
paleoclimate.
June insolation at 66°N
Antarctic temperature
Sea level
Observation
ModelSlide44
The last million years: glacial interglacial cycles
The glacial-interglacial
variations in the atmospheric CO
2
concentration
reach 90 ppm.
This corresponds to a radiative forcing of
2 W m
-2
.
Figure
from
Ciais
et al. (2013
).
Chapter 5 Page
44
CO
2
changes (ppm)
Mechanisms contributing to the glacial to interglacial difference in CO
2
. Slide45
Millennial-scale variability during glacial periods
Dansgaard-Oeschger events
are abrupt events characterized by warming in Greenland of several degrees in
a few
decades.
Time series of δ
18
O measurements obtained in the framework of the North Greenland Ice Core Project (NGRIP, North Greenland Ice Core Project Members, 2004).
Chapter 5 Page
45
Dansgaard-Oeschger events
have a
global impact
.Slide46
Millennial-scale variability during glacial periods
Heinrich events
correspond to a massive iceberg discharge that let thick
layers of debris in the sediments of the North Atlantic.
Chapter 5 Page
46
Schematic representation of the massive iceberg release leading to the sediments deposits characteristics of Heinrich
events.Slide47
Millennial-scale variability during glacial periods
The millennial-scale variability is likely related to the
ice sheet dynamics
and the
oceanic circulation
.
Chapter 5 Page
47
Schematic representation of the
processes potentially occurring during Dansgaard-Oeschger events.Slide48
The last deglaciation
The
increase in CO
2
concentration
appears
synchronous
with the temperature rise in
Antarctica.
Chapter 5 Page
48
Times series of
CO
2
concentration measured in the EDC ice core and
Antarctic
temperature estimated from a composite of five Antarctic ice cores records during the deglaciation. Data from
Parrenin
et al. (2013).
Antarctic temperature
CO
2
concentrationSlide49
The last deglaciation
The deglaciation is also characterized by
millennial-scale variability
.
Chapter 5 Page
49
Time
series of temperature averaged over different latitudes bands reconstructed from a compilation of various proxies.
Figure
from
Shakun
et al. (2012).
Younger DryasSlide50
The current interglacial
–The Holocene
The
maximum of summer
insolation at high latitudes over the Holocene was reached at the beginning of the
interglacial.
Chapter 5 Page
50
Deviations from present-day values at 10ka BP of the
daily insolation
for calendar months (in Wm
-2
). Data from Berger (1978). Figure from Marie-France Loutre.Slide51
The current interglacial
–The Holocene
The
Holocene Thermal Optimum
is found
between 9 and 6
ka
BP in the Northern Hemisphere.
Northern Hemisphere
summer monsoon
was stronger in the early and mid-Holocene.
Chapter 5 Page
51
Difference of precipitation (mm/d) between Mid-Holocene (6000
yr
BP) and preindustrial conditions for the ensemble mean of PMIP2 simulations. Figure from
Braconnot
et al. (2007).Slide52
The past 2000 years
The
last 30 years
were likely the warmest 30-year period of the last 1400 years in the Northern Hemisphere
Chapter 5 Page
52
Reconstructions of
Northern Hemisphere temperatures during the last 2000
years. Figure
from Masson-
Delmotte
et al. (2013).
The
global
mean temperature
shows relatively
mild conditions
between
950 and 1250 AD
and cold conditions between
1450 and 1850
AD
.Slide53
The past 2000 years
Chapter 5 Page
53
Comparison of simulated and reconstructed changes over past millennium in the Northern Hemisphere.
Figure
from Masson-
Delmotte
et al. (2013).
When driven by
natural and anthropogenic forcings
, model are able to reproduce the observed changes.
Medieval Climate Anomaly
Little Ice Age
20
th
century
Range of
the
reconstructionsSlide54
The past 2000 years
Chapter 5 Page
54
Temperature reconstructions for seven continental-scale regions.
Figure
from PAGES2K (2013).
Some characteristics are common, but the
warm and cold periods
are
not synchronous
between the different regions
.Slide55
The past 2000 years
Chapter 5 Page
55
Surface temperature anomaly (°C) in the Arctic
over
the last millennium
in
an ensemble of 10
simulations using the same model
driven by the same natural and anthropogenic forcings.
A decadal smoothing has been applied to the series. Data
from
Crespin
et al. (2013).
The
internal
variability
is
responsible of some of the warm and cold periods in the different regions.
Two simulations are in blue and
red
.
Eight simulations are in grey. Slide56
The last century
Chapter 5 Page
56
Global mean annual surface temperature
(°
C) from 1850 to 2012 relative to the 1961 to 1990 mean, from 3 different
datasets. Figure
from Hartmann et al. (
2014
)
.
The
linear trend
of
global mean temperature over the years 1901-2012
gives an
increase
of 0.89°C
over that
period.Slide57
The last century
Chapter 5 Page
57
Linear trend of annual temperatures between 1901 and 2012 in HadCRUT4 and GISS datasets (°C over the period
). Figure
from Hartmann et al. (
2014
)
.
The warming is seen in nearly all the regions with generally a slower warming over ocean than over land.Slide58
Detection and attribution of recent climate changes
Chapter 5 Page
58
The
anthropogenic
origin of the
rise in atmospheric CO
2
concentration since the 19th century is
unequivocal.
The
part of the
recent temperature changes
compatible
with the natural
variability can be estimated using various techniques
.Slide59
Detection and attribution of recent climate changes
Chapter 5 Page
59
Simulations using various
combinations of forcings
can be compared to observations.
Models with natural forcings only
Observations
Models with natural and anthropogenic forcings
Figure from Jones et al. (2013)Slide60
Detection and attribution of recent climate changes
Chapter 5 Page
60
Observations
are
not
compatible
with the hypothesis stating that the changes in climate observed recently are in the range of
natural variability
on decadal to centennial timescales.
Observations
are
compatible
with the hypothesis that anthropogenic forcing is needed to explain the recent temperature changes. Slide61
Detection and attribution of recent climate changes
Chapter 5 Page
61
Detection
and attribution
methods represent the
observed changes
as the sum of
the response
to different
forcings
and
internal variability
.
Observations
Spatial
dimensions
Number of forcings studied
Scaling coefficient
Response to forcing
i
.
Internal variability
“Fingerprint”
TimeSlide62
Detection and attribution of recent climate changes
Chapter 5 Page
62
Example: simple
,
idealised
situation,
considering
an
observed time series T(t)
Simple illustration of the detection and attribution method. The observed time series
T(t
) =
β
1
Resp
1
(t) +
β
2
Resp
2
(t)+u(t
).
In the chosen example, the coefficient of the linear combination are β
1
=0.6 and β
2
=1.2.Slide63
Detection and attribution of recent climate changes
Chapter 5 Page
63
The
contribution of the
increase in greenhouse gas
concentrations in the atmosphere in the recent
warming
can be clearly
detected
.
Scaling coefficient in a detection and attribution
study. Data
from Jones et al. (2013).
Greenhouse gases
Other anthropogenic forcings
Natural forcings